A variety of automatic speech recognition (ASR) systems exist for recognizing speech to perform functions such as creating transcripts of the speech and controlling the operation of a computer. In one common configuration for such systems, a microphone is connected directly to a desktop computer or other computing device which executes automatic speech recognition software for recognizing the user's speech and acting on the results of that recognition. In another common configuration of such systems, the user makes a telephone call and speaks into a telephone, and an automatic speech recognition system remote from the user recognizes the user's speech and acts on the results of that recognition.
Recently a much wider variety of computing devices have become available having varying features and costs. For example, in addition to desktop and laptop computers (which typically must be connected to an external microphone, purchased separately, to capture speech), vendors now provide a wide variety of personal digital assistants (PDAs), smartphones, and tablet computers, all of which are capable of connecting to the Internet and other networks (often wirelessly), all of which are capable of executing custom applications to some extent, and some of which contain built-in microphones.
What is needed, therefore, are improved techniques for making use of a variety of computing technologies to provide automatic speech recognition capabilities that provide the right combination of recognition quality, recognition speed, and cost of ownership.